Time-based visualization for network virtualization platform

ABSTRACT

Concepts and technologies disclosed herein are directed to time-based visualizations for network virtualization platforms (“NVPs”). A computer system can obtain data associated with an NVP. The data can include present state data associated with a present state of the NVP, past state data associated with a past state of the NVP, and future state data associated with a predicted future state of the NVP. The computer system can generate a visualization of the data associated with the NVP. The computer system can present a temporal management function that includes a plurality of selections representative of the present state, the past state, and the predicted future state. The computer system can receive a selection, from the plurality of selections, of the present state, the past state, or the predicted future state. The computer system can manipulate the visualization in accordance with the selection and output the visualization.

BACKGROUND

Software-defined networking (“SDN”) is an architectural framework forcreating intelligent networks that are programmable, application aware,and more open. SDN provides an agile and cost-effective communicationsplatform for handling the dramatic increase in data traffic on carriernetworks by providing a high degree of scalability, security, andflexibility. SDN provides several benefits. SDN can allow for thecreation of multiple virtual network control planes on common hardware.SDN can help extend service virtualization and software control intomany existing network elements. SDN enables applications to request andmanipulate services provided by the network and to allow the network toexpose network states back to the applications. SDN exposes networkcapabilities through application programming interfaces (“APIs”), makingthe control of network equipment remotely accessible and modifiable viathird-party software clients using open protocols such as OpenFlow,available from Open Network Forum (“ONF”).

User-defined, on-demand cloud services and user digital experienceexpectations are driving planning and deployment of network functionalvirtualization and service-centric SDN among global telecommunicationsservice providers. Network Virtualization Platforms (“NVPs”) aredeployed in information technology (“IT”) data centers, network centraloffices, and other network points of presence (“POPs”) to acceleratedeployment of on-demand user service and virtualized network functions.An NVP is a shared virtualized infrastructure that supports multipleservices and network applications (including real-time and non-real-timeapplications).

Combining SDN and NVP functionality provides a highly complex anddynamic set of relationships between virtual, logical, and physicalresources. Autonomous controls and real-time service path steering,workload, creation, distribution, and destruction are inherent NVPcapabilities, but currently no unified and holistic method exists forhuman operators to understand, model, and design service paths and tounderstand and control the operations of the environment. Currentlyavailable solutions are dominated by tools and techniques developed tosupport traditional information technology and network domains, which,in comparison, are relatively simple and static, and are thereforeill-suited to SDN/NVP and similar environments. The new dimensions ofSDN/NVP require a new dimension of human insight and control.

SUMMARY

Concepts and technologies disclosed herein are directed to time-basedvisualizations for network virtualization platforms (“NVPs”). Accordingto one aspect disclosed herein, a computer system can obtain dataassociated with an NVP. The data can include present state dataassociated with a present state of the NVP, past state data associatedwith a past state of the NVP, and future state data associated with apredicted future state of the NVP. The computer system can generate avisualization of the data associated with the NVP. The computer systemcan present a temporal management function that includes a plurality ofselections representative of the present state, the past state, and thepredicted future state. The computer system can receive, via thetemporal management function, a selection, from the plurality ofselections, of the present state, the past state, or the predictedfuture state. The computer system can manipulate the visualization inaccordance with the selection and output the visualization.

In some embodiments, the visualization includes a three-dimensionalvisualization. The three-dimensional visualization can include a centralcube visualization. The central cube visualization can include aplurality of smaller cube visualizations. Each of the plurality ofsmaller cube visualizations can include a node representative of anapplication. The application can be executable by at least a portion ofa plurality of resources of the NVP. The central cube visualization, insome embodiments, includes a plurality of networking links between atleast a portion of the plurality of applications of the plurality ofsmaller cube virtualizations.

In some embodiments, the data further includes data associated with atopology of the plurality of resources of the NVP. In these embodiments,the computer system can receive a request to instantiate a serviceinstance of a service provided by the NVP. In response to the request,the computer system can generate a logical topology view of the centralcube visualization. The computer system can output the logical topologyview of the central cube visualization. The logical topology view caninclude at least a portion of the topology of the plurality of resourcesof the NVP. The logical topology view can represent a service path. Theservice path can include and identify a set of the plurality ofresources utilized by the service.

In some embodiments, the temporal management function can include atimeline. Each of the plurality of selections can include a timeinterval. The time intervals can be in increments of seconds, minutes,days, hours, weeks, months, years, or any division or multiple thereof.In some embodiments, the computer system can manipulate thevisualization in accordance with selection by transitioning, at least inpart, between the present state, the past state, and the future state.This may appear as if the visualization is morphing from one state toanother. For example, a user may pause, fast forward (towards the futurestate), or rewind (towards the past state) by selecting different timeintervals.

It should be appreciated that the above-described subject matter may beimplemented as a computer-controlled apparatus, a computer process, acomputing system, or as an article of manufacture such as acomputer-readable storage medium. These and various other features willbe apparent from a reading of the following Detailed Description and areview of the associated drawings.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intendedthat this Summary be used to limit the scope of the claimed subjectmatter. Furthermore, the claimed subject matter is not limited toimplementations that solve any or all disadvantages noted in any part ofthis disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating aspects of an illustrativeoperating environment for implementing the various concepts andtechnologies disclosed herein.

FIG. 2 is a block diagram illustrating aspects of a visualizationcomponent used by a computer system to generate a visualization of dataassociated with an NVP, according to an illustrative embodiment.

FIGS. 3A-3H are diagrams illustrating aspects of various views of anexample visualization, according to an illustrative embodiment.

FIG. 4 is a flow diagram illustrating aspects of a method for generatinga visualization of NVP data, according to an illustrative embodiment.

FIG. 5 is a flow diagram illustrating aspects of a method for adjustinga new view of a visualization of NVP data, according to an illustrativeembodiment.

FIG. 6 is a flow diagram illustrating aspects of a method for generatinga logical topology view of a visualization of NVP data, according to anillustrative embodiment.

FIG. 7 is a flow diagram illustrating aspects of a method for generatingan actual topology view of a visualization of NVP data, according to anillustrative embodiment.

FIG. 8 is a flow diagram illustrating aspects of a method for generatinga present view of a visualization of NVP data, according to anillustrative embodiment.

FIG. 9 is a flow diagram illustrating aspects of a method for generatinga past view of a visualization of NVP data, according to an illustrativeembodiment.

FIG. 10 is a flow diagram illustrating aspects of a method forgenerating a future view of a visualization of NVP data, according to anillustrative embodiment.

FIG. 11 is a flow diagram illustrating aspects of a method formanipulating a visualization of NVP data based upon time, according toan illustrative embodiment.

FIG. 12 is a block diagram illustrating a plurality of modulesassociated with an NVP monitoring application and a visualizationcomponent that can be executed by a computer system to perform variousoperations to facilitate user interaction with a visualization,according to an illustrative embodiment.

FIG. 13 is a block diagram illustrating an example computer systemcapable of implementing aspects of the embodiments presented herein.

FIG. 14 schematically illustrates a network, according to anillustrative embodiment.

FIG. 15 is a block diagram illustrating an example mobile device andcomponents thereof, according to an illustrative embodiment.

FIG. 16 is a block diagram illustrating an illustrative machine learningsystem capable of implementing aspects of the concepts and technologiesdisclosed herein.

FIG. 17 is a diagram illustrating a temporal management control thatallows a user to control the playback of a data visualization, accordingto an illustrative embodiment.

DETAILED DESCRIPTION

Combining SDN and NVP functionality provides a highly complex anddynamic set of relationships between virtual, logical, and physicalresources. Autonomous controls and real-time service path steering,workload, creation, distribution, and destruction are inherent NVPcapabilities but currently no unified and holistic method exists forhuman operators to understand, model, and design service paths and tounderstand and control the operations of the environment. Currentlyavailable solutions are dominated by tools and techniques developed tosupport traditional information technology and network domains, which,in comparison, are relatively simple and static, and are thereforeill-suited to SDN/NVP and similar environments. The new dimensions ofSDN/NVP and similar environments require a new dimension of humaninsight and control.

The concepts and technologies disclosed herein facilitate relatingphysical and logical aspects of SDN/NVP and applications for use inservice design, instantiation, and operations by both internal users andexternal customers. The concepts and technologies described herein, insome embodiments, provide a three-dimensional cube metaphor that allowsvisualization, navigation, temporal views, and manipulation of servicelogic specified by the alignment of service paths onto a service graph.Moreover, the application of virtual reality and augmented realitytechnologies provides an intuitive, effective, and highly-differentiatedexperience for network management.

While the subject matter described herein may be presented, at times, inthe general context of program modules that execute in conjunction withthe execution of an operating system and application programs on acomputer system, those skilled in the art will recognize that otherimplementations may be performed in combination with other types ofprogram modules. Generally, program modules include routines, programs,components, data structures, computer-executable instructions, and/orother types of structures that perform particular tasks or implementparticular abstract data types. Moreover, those skilled in the art willappreciate that the subject matter described herein may be practicedwith other computer systems, including hand-held devices, mobiledevices, wireless devices, multiprocessor systems, distributed computingsystems, microprocessor-based or programmable consumer electronics,minicomputers, mainframe computers, routers, switches, other computingdevices described herein, and the like.

While connections are shown between some of the components illustratedin FIG. 1, it should be understood that some, none, or all of thecomponents illustrated in FIG. 1 can be configured to interact with oneother to carry out various functions described herein. Thus, it shouldbe understood that FIG. 1 and the following description are intended toprovide a general understanding of a suitable environment in whichvarious aspects of embodiments can be implemented, and should not beconstrued as being limiting in any way.

Referring now to FIG. 1, aspects of an operating environment 100 forimplementing various embodiments of the concepts and technologiesdisclosed herein will be described. The operating environment 100 shownin FIG. 1 includes a computer system 102 operating on or incommunication with an NVP 104 to provide functionality in accordancewith the concepts and technologies disclosed herein to visualize NVPdata 106 associated with and received from the NVP 104, including, forexample, data associated with one or more services 108-108K provided, atleast in part, by one or more applications 110-110L operating within anSDN network 112 created and managed, at least in part, by the NVP 104.It should be understood that the concepts and technologies disclosedherein, while described in context of the services 108 provided, atleast in part, by the applications 110 operating within the SDN network112 created and managed, at least in part, by the NVP 104, areapplicable to any type of service. As such, the specific references tovisualizing the NVP data 106 should not be construed as being limitingin any way.

According to various implementations of the concepts and technologiesdisclosed herein, the computer system 102 can include a user computingdevice, such as a tablet computing device, a personal computer (“PC”), adesktop computer, a laptop computer, a notebook computer, a cellularphone or smartphone, other mobile computing devices, a personal digitalassistant (“PDA”), or the like. Example architectures of the computersystem 102 are illustrated and described herein below with reference toFIGS. 13 and 15. The functionality of the computer system 102 can beprovided, at least in part, by a cloud-based computing platform that canbe provided by one or more application servers, web servers, datastorage systems, network appliances, dedicated hardware devices, and/orother server computers or computing devices, which might, in someembodiments, leverage compute, memory, and/or other resources of the NVP104 to perform operations described herein. In light of the abovealternative embodiments of the computer system 102, it should beunderstood that this example is illustrative and should not be construedas being limiting in any way.

The computer system 102 can be configured to execute an operating system114 and one or more application programs such as, for example, an NVPmonitoring application 116, a visualization component 118, a temporalmanagement component 120, and/or other application programs. Theoperating system 114 is a computer program for controlling the operationof the computer system 102. The application programs are executableprograms configured to execute on top of the operating system 114. Insome embodiments, at least a portion of the NVP monitoring application116 functionality, the visualization component 118 functionality, and/orthe temporal management component 120 functionality is included in theoperating system 114. In some other embodiments, at least a portion ofthe NVP monitoring application 116 functionality, the visualizationcomponent 118 functionality, and/or the temporal management component120 functionality is included in the NVP 104, wherein the computersystem 102 accesses the functionality via a communications interface.

In some embodiments, the visualization component 118 can be implementedas part of the NVP monitoring application 116. In some embodiments, thevisualization component 118 can be implemented as a component separatefrom the NVP monitoring application 116. In some embodiments, thevisualization component 118 can be provided as a stand-aloneapplication. Similarly, in some embodiments, the temporal managementcomponent 120 can be implemented as part of the NVP monitoringapplication 116 or a component separate from the NVP monitoringapplication 116. In some embodiments, the temporal management component120 can be provided as a stand-alone application. Thus, while the NVPmonitoring application 116, the visualization component 118, and thetemporal management component 120 are illustrated as components of thecomputer system 102, it should be understood that each of thesecomponents, or combinations thereof, may be embodied as or instand-alone devices or components thereof operating on or incommunication the computer system 102. Thus, the illustrated embodimentis illustrative and should not be construed as being limiting in anyway.

In some embodiments, the visualization component 118 and/or the temporalmanagement component 120 can be implemented as a plugin or add-in forthe NVP monitoring application 116. In some other embodiments, thevisualization component 118 and/or the temporal management component 120can include a service and/or set of application programming interfaces(“APIs”) that can provide the functionality described herein. Thus, itshould be appreciated that the visualization component 118 and/or thetemporal management component 120 can be implemented as hardware,software, or a combination thereof.

The NVP 104 is a shared infrastructure that can support multipleservices, such as the services 108, and multiple network applications,such as the applications 110 (including real-time and non-real-timeapplications). The NVP 104 can utilize cloud sharing constructs tovirtualize network functions by decoupling hardware and software, makingnetworks, such as the SDN network 112, more flexible and physicallyuniform by minimizing dependence upon hardware constraints. The NVP 104uses SDN to provide programmability and abstraction of underlyinghardware complexity and to separate management and control planes fromthe data plane.

The applications 110 can include, but are not limited to, one or moreapplications that provide or utilize, at least in part, one or more ofthe services 108, such as, for example, domain name service (“DNS”),network address translation (“NAT”), remote add/drop multiplexing,remote authentication dial-in user service (“RADIUS”), firewall,encryption/decryption, network content packet routing, dynamic hostconfiguration protocol (“DHCP”), lightweight directory access protocol(“LDAP”), content routing in either or both of the control and dataplanes, and route reflecting in either or both the control and dataplanes. The services 108 also can include one or more real-time servicessuch as, but are not limited to, voice over internet protocol (“VoIP”)service, streaming video service, videoconferencing service, onlinegaming service, chatting service, instant messaging (“IM”) service, andthe like in the service plane. Both synchronous and asynchronous (e.g.,transactional) services are contemplated.

The illustrated NVP 104 includes a hardware resource layer 121, avirtualization/control layer 122, and a virtual resource layer 124 thatwork together to perform operations as will be described in detailherein. The hardware resource layer 121 provides hardware resources,which, in the illustrated embodiment, include one or more computeresources 126, one or more memory resources 128, and one or more otherresources 130.

The compute resource(s) 126 can include one or more hardware componentsthat perform computations to process data, and/or to executecomputer-executable instructions of one or more application programs,operating systems, and/or other software, including the applications 110to provide, at least in part, the services 108. The compute resources126 can include one or more central processing units (“CPUs”) configuredwith one or more processing cores. The compute resources 126 can includeone or more graphics processing unit (“GPU”) configured to accelerateoperations performed by one or more CPUs, and/or to perform computationsto process data, and/or to execute computer-executable instructions ofone or more application programs, operating systems, and/or othersoftware that may or may not include instructions particular to graphicscomputations. In some embodiments, the compute resources 126 can includeone or more discrete GPUs. In some other embodiments, the computeresources 126 can include CPU and GPU components that are configured inaccordance with a co-processing CPU/GPU computing model, wherein thesequential part of an application executes on the CPU and thecomputationally-intensive part is accelerated by the GPU. The computeresources 126 can include one or more system-on-chip (“SoC”) componentsalong with one or more other components, including, for example, one ormore of the memory resources 128, and/or one or more of the otherresources 130. In some embodiments, the compute resources 126 can be orcan include one or more SNAPDRAGON SoCs, available from QUALCOMM of SanDiego, Calif.; one or more TEGRA SoCs, available from NVIDIA of SantaClara, Calif.; one or more HUMMINGBIRD SoCs, available from SAMSUNG ofSeoul, South Korea; one or more Open Multimedia Application Platform(“OMAP”) SoCs, available from TEXAS INSTRUMENTS of Dallas, Tex.; one ormore customized versions of any of the above SoCs; and/or one or moreproprietary SoCs. The compute resources 126 can be or can include one ormore hardware components architected in accordance with an ARMarchitecture, available for license from ARM HOLDINGS of Cambridge,United Kingdom. Alternatively, the compute resources 126 can be or caninclude one or more hardware components architected in accordance withan x86 architecture, such an architecture available from INTELCORPORATION of Mountain View, Calif., and others. Those skilled in theart will appreciate the implementation of the compute resources 126 canutilize various computation architectures or combinations thereof, andas such, the compute resources 126 should not be construed as beinglimited to any particular computation architecture or combination ofcomputation architectures, including those explicitly disclosed herein.

The memory resource(s) 128 can include one or more hardware componentsthat perform storage operations, including temporary or permanentstorage operations. In some embodiments, the memory resource(s) 128include volatile and/or non-volatile memory implemented in any method ortechnology for storage of information such as computer-readableinstructions, data structures, program modules, or other data disclosedherein. Computer storage media includes, but is not limited to, randomaccess memory (“RAM”), read-only memory (“ROM”), erasable programmableROM (“EPROM”), electrically erasable programmable ROM (“EEPROM”), flashmemory or other solid state memory technology, CD-ROM, digital versatiledisks (“DVD”), or other optical storage, magnetic cassettes, magnetictape, magnetic disk storage or other magnetic storage devices, or anyother medium which can be used to store data and which can be accessedby the compute resources 126.

The other resource(s) 130 can include any other hardware resources thatcan be utilized by the compute resources(s) 126 and/or the memoryresource(s) 128 to perform operations described herein. The otherresource(s) 130 can include one or more input and/or output processors(e.g., network interface controller or wireless radio), one or moremodems, one or more codec chipset, one or more pipeline processors, oneor more fast Fourier transform (“FFT”) processors, one or more digitalsignal processors (“DSPs”), one or more speech synthesizers, and/or thelike.

The hardware resources operating within the hardware resource layer 121can be virtualized by one or more virtual machine monitors (“VMMs”)132-132M (also known as “hypervisors;” hereinafter “VMMs 132”) operatingwithin the virtualization/control layer 122 to manage one or morevirtual resources that reside in the virtual resource layer 124. TheVMMs 132 can be or can include software, firmware, and/or hardware thatalone or in combination with other software, firmware, and/or hardware,manages one or more virtual resources operating within the virtualresource layer 124.

The virtual resources operating within the virtual resource layer 124can include abstractions of at least a portion of the compute resources126, the memory resources 128, the other resources 130, or anycombination thereof. These abstractions are referred to herein asvirtual machines (“VMs”). It should be understood, however, that othercontainer technologies can be used and are contemplated. In theillustrated embodiment, the virtual resource layer 124 includes VMs134-134N (hereinafter “VMs 134”). The VMs 134 can execute theapplications 110 to provide, at least in part, the services 108. Each ofthe VMs 134 can execute one or more of the applications 110 or one ormore portions thereof. For example, one or more of the VMs 134 canexecute one or more of the applications 110 to utilize or provide, atleast in part, the services 108 such as, but not limited to, DNS,RADIUS, DHCP, LDAP, content routing in either or both of the control anddata planes, and route reflecting in either or both the control and dataplanes. The applications 110 also can include one or more applicationsthat provide, at least in part, one or more real-time services such as,but are not limited to, VoIP, streaming video service, videoconferencingservice, online gaming service, chatting service, IM service, and thelike in the service plane.

The NVP data 106 can include any data associated with the NVP 104. Forexample, the NVP data 106 can be or can include data associated with theoperational state(s) and configuration(s) of one or more components ofthe NVP 104, such as the operational states and configurations of thevirtual resources operating within the virtual resource layer 124. TheNVP data 106 also can include data associated with applicationresources, such as one or more of the applications 110-110L.

The NVP 104 can provide the NVP data 106 to the computer system 102periodically, continuously, and/or upon request. The NVP monitoringapplication 116 can, in some embodiments, include functionality toenable a user 136 to schedule periodic retrieval of the NVP data 106from the NVP 104 or to request the NVP data 106 on-demand. The NVP 104,in some embodiments, can be configured to report the NVP data 106 to thecomputer system 102 periodically or in response to an event, such as achange of an operational state and/or of a configuration of one or moreof the virtual resources operating within the virtual resource layer 124and/or one or more application resources instantiated in the SDN network112.

The NVP monitoring application 116 can receive the NVP data 106 and canprovide at least a portion of the NVP data 106 to the visualizationcomponent 118. The visualization component 118 alternatively can requestthe NVP data 106 from the NVP monitoring application 116. In eithercase, the visualization component 118 can obtain the NVP data 106,generate, based upon the NVP data 106, a visualization 138 of the NVPdata 106, and output the visualization 138 via a user interface (“UI”)140 of the visualization component 118 via a display 142, an extendedreality (“XR”) system 144, or a combination thereof. The user 136 caninteract with the UI 140 of the visualization component 118 to view andinteract with the visualization 138. In doing so, the user 136 can exertinfluence upon the automation and control of the NVP 104 or at least aportion thereof.

The visualization 138 can be generated by any software frameworkdesigned for the creation and development of graphics. Some examplesoftware frameworks include, but are not limited to, AUTOCAD (availablefrom AUTODESK), BLENDER (available from the open source BLENDERFOUNDATION), UNREAL ENGINE (available from EPIC GAMES), UNITY (availablefrom UNITY TECHNOLOGIES), CRYENGINE (available from CRYTEK), HAVOKVISION ENGINE (available from HAVOK), other proprietary softwareframeworks, open source software frameworks, combinations thereof, andthe like. Those skilled in the art will appreciate the wide range ofgraphical fidelity, visual styles, and other attributes thevisualization 138 might have, including color, shape, texture, space,form, dynamics (e.g., bouncing, flashing, and the like), and otherdesign and/or interaction elements. As such, further details in thisregard are not provided herein since these are mere design decisions.

The display 142 is an output device configured to present information ina visual form. In some embodiments, the display 142 is two-dimensionalor three-dimensional rendering device using a liquid crystal display(“LCD”) utilizing any active or passive matrix technology and canutilize any backlighting technology. In some embodiments, the display142 is an organic light emitting diode (“OLED”) display. The display 142can be embodied with other display technologies. In some embodiments,the display 142 is part of the XR system 144. For example, the XR system144 may be a virtual reality (“VR”) headset such as one of the OCULUSfamily of VR headsets (available from FACEBOOK). As such, the examplesprovided above should not be considered limiting in any way.

The XR system 144 can provide an augmented reality through which atleast a portion of a physical, real-world environment is augmented toinclude the visualization 138. The visualization 138 can be presentedvia the XR system 144 over and/or spatially integrated with real-worldobjects of the physical, real-world environment. In these embodiments,the XR system 144 can utilize a camera component (not shown) to providea live view of the physical, real-world environment to be augmented withthe visualization 138. In other embodiments, the XR system 144 canprovide a non-live view of a physical, real-world environment. Thenon-live view can present a physical, real-world environment as a staticimage representative of a past reality that can be augmented with thevisualization 138.

The XR system 144 can be in communication with the computer system 102via a wireless or wired connection through which data, such as the NVPdata 106 and other data associated with the visualization 138, can beshared. The XR system 144 can function as a stand-alone system thatutilizes on-board computing components to perform operations to presentand facilitate manipulation of an augmented reality augmented with thevisualization 138, or alternatively, can leverage the computingresources of the computer system 102, or even at least a portion of thehardware resources in the hardware resource layer 121 of the NVP 104 toperform such operations.

The XR system 144, in some embodiments, is or includes a camera (e.g., astill camera and/or video camera), a sensor (e.g., an accelerometer, aglobal positioning system sensor, a solid state compass, or the like), adisplay (e.g., an integrated display, a head-mounted display, aneyeglasses display, a head-up display, an external monitor, a projectionsystem, or a holographic display), an input device, the like, or anycombination thereof. In some embodiments, the XR system 144 is orincludes a wearable computing device that includes an integrated displaythrough which to present the visualization 138 via an augmented reality.The XR system 144, in these embodiments, can be GOOGLE GLASS, availablefrom GOOGLE INC., or MICROSOFT HOLOLENS, available from MICROSOFT CORP.Other devices, such as mobile telephones, smartphones, tablet computers,slate computers, smart watches, laptop computers, notebook computers,ultrabook computers, netbook computers, computers of other form factors,computing devices of other form factors, other computing systems, othercomputing devices, and/or the like, can be configured to execute one ormore XR applications to function as the XR system 144 described herein.

The XR system 144 can provide a computer-generated environment (alsoreferred to herein as a “virtual reality” or “VR” environment) that theuser 136 can explore. The virtual environment can be or can include thevisualization 138. A VR environment can include a computer-generatedrepresentation or at least an approximation of at least a portion of aphysical, real-world environment with the visualization 138 integratedwithin. The VR environment can be at least partially different from thephysical, real-world environment of which the VR environment isrepresentative with the visualization 138 integrated within. The VRenvironment can include virtual objects not found in the correspondingphysical, real-world environment. Lighting effects such light bloom andother effects such as depth-of-field can be applied to the VRenvironment to create atmosphere. Moreover, natural phenomena such asgravity and momentum can be simulated in the virtual environment. Thesenatural phenomena can be simulated, for example, when the user 136interacts with the visualization 138.

The XR system 144, in some embodiments, is or includes a display (e.g.,an integrated display, a head-mounted display, an eyeglasses display, ahead-up display, an external monitor, or a projection system), an inputdevice, a combination thereof, or the like. In some embodiments, the XRsystem 144 is OCULUS RIFT (available from FACEBOOK), GOOGLE CARDBOARD(available from GOOGLE), HTC VIVE (available from HTC), PLAYSTATION VR(available from SONY), or the like.

The visualization 138 can be presented on the display 142, via the XRsystem 144 and can be interacted with by the user 136 through one ormore input devices 148. Although shown as being external to the computersystem 102, the display 142, the XR system 144, and the input device(s)148 can be implemented as part of the computer system 102, the display142, and/or the XR system 144. The input device(s) 148 can be or caninclude one or more touchscreens, one or more multi-touch touchscreens,one or more keyboards, one or more computer mice, one or more gamecontrollers, one or more joysticks, one or more touchpads, one or moregesture devices (e.g., MICROSOFT KINECT or MICROSOFT HOLOLENS, bothavailable from MICROSOFT CORPORATION), combinations thereof, or thelike.

The visualization 138, in some embodiments, includes a three-dimensionalvisualization. The visualization 138 may change over time. Thethree-dimensional visualization can include a central cubevisualization. The central cube visualization can include athree-dimensional assemblage of stacks of smaller cubes, eachrepresenting one or more application resources such as one or more ofthe applications 110. At the core of each smaller cube in thevisualization 138 can be a node representing the applicationresource(s). Networking among the application resources can berepresented as links between the nodes of the cubes. When referencingthe visualization 138 in the description below, a central cubevisualization as described above will provide the context. It should beunderstood, however, that other shapes can be used by the visualizationcomponent 118 to convey, to the user 136, similar information. Someillustrative examples of the visualization 138 are illustrated withreference to FIGS. 3A-3H, which are described in greater detail below.

The visualization 138 can provide a service graph. A “service graph,” asused herein, is a collection of available resources (such as applicationresources embodied as the applications 110) along with sequencing andrelationships available to be used to process data plane servicerequests to instantiate a service instance of one or more of theservices 108. A service graph describes the actual topology of theresources instantiated and operationalized by the NVP 104 within the SDNnetwork 112. A service graph can be viewable as a full view of thevisualization 138. An illustrative example of a service graph is shownin FIG. 3B.

A “service path,” as used herein, is a collection of specific resourcesfrom the service graph along with sequencing and relationships used toprocess a specific data plane service request. A service path describesa logical topology of the resources included in a particular instance ofa service, such as one of the services 108. The illustrative servicepaths provided herein follow a flow convention of left-to-right,although right-to-left and/or other flows are contemplated. A logicalview of a service path can be provided by a face plane view of thevisualization 138. An illustrative example of a logical view of aservice path as a face plane view of a central cube visualization isshown in FIG. 3C. The visualization 138 can provide a plurality oflayers of the face plane view. Each of the layers can represent aphysical technical plant (“TeP”) location. Physical TePs can be or caninclude one or more telco central offices (“COs”), one or more datacenters, one or more outside plant environments (e.g., huts, bunkers,poles, and the like), customer premises locations, and the like. Thespecific resources in a specific TeP location that are processing aparticular data plane service request can be identified by sliding outthe corresponding layer for examination by the user 136, or bynavigating into the visualization 138.

A network (or administrative domain) wide view across all TePs can beprovided by a top plane view of the visualization 138. A top plane viewidentifies the collection of all potential physical resources, such asprovided in the hardware resource layer 121 of the NVP 104, available toprocess a particular data plane service request, as well as the specificresources that are processing a particular data plane service request.This view is perhaps most valuable for steering service requests, whichwould be enabled by disconnecting a network link from an applicationresource in one TeP and reconnecting it to the same type of resource inanother TeP. An illustrative example of this view is shown in FIG. 3E.Service logic can be defined by aligning a service path onto a servicegraph. “Service Logic,” as used herein, is what aligns a service pathonto a service graph. Data plane traffic steering/engineering is oneaspect of service logic and can be accomplished by adding and connectingapplication resources across and within TePs. Service logic can beconstrained by affinity/anti-affinity rules, quality of service (“QoS”)parameters (e.g., latency), regulatory, business needs, and the like.Service logic controls embedded within the visualization 138 can bemanipulated by operators and/or customers, such as the user 136, toinfluence the data plane traffic of the underlying NVP, such as the NVP104.

The user 136 can interact with the visualization 138 through the UI 140using various actions. The actions can include user input received bythe computer system 102 via the display 142, the XR system 144, theinput device(s) 148, or some combination thereof from the user 136. Theactions can include movement actions such as, but not limited to, panup, pan down, pan left, pan right, rotate clockwise, rotatecounter-clockwise, tilt down, tilt up, zoom in, zoom out, field-of-viewincrease, field-of-view decrease, and the like. The movement actions canbe used to navigate the visualization 138. The actions can include timemanipulations controlled via the temporal management component 120. Thetime manipulations can allow the user 136 to navigate the visualization138 through time to explore the NVP 104 at different times such as inthe past, present, and future. Other actions to add, delete, and/ormodify at least a portion of the visualization 138 also arecontemplated.

In some embodiments, the user 136 might perform gestures as user inputto perform one or more actions. Gestures might be performed usinghand-held controllers, optically recognized, or by touching a single ormulti-touch touchscreen. Gestures might be open-space gestures throughwhich the user 136 utilizes at least a portion of his or her body asuser input to perform one or more actions in space. For example, theinput device 148 embodied as KINECT or HOLOLENS can enable the user 136to perform such gestures to interact with the visualization 138. Severalgestures will now be described. It should be understood that thesegestures are illustrative and are not intended to limit the scope of theappended claims. Moreover, the described gestures, additional gestures,and/or alternative gestures may be implemented in software for use bythe computer system 102 via the display 142, the XR system 144, theinput device(s) 148, or some combination thereof. As such, a developermay create gestures that are specific to a particular applicationprogram, such as the visualization component 118.

In some embodiments, the input device 148 embodied as a touchscreen cansupport a tap gesture in which the user 136 taps the touchscreen once onan item presented on the display 142 to select at least a portion of thevisualization 138. In some embodiments, the touchscreen supports adouble tap gesture in which the user 136 taps the touchscreen twice onan item presented on the display 142 to perform an action such as, butnot limited to, zooming into or zooming out of the visualization 138 instages. In some embodiments, the touchscreen supports a tap and holdgesture in which the user 136 taps the touchscreen and maintains contactfor at least a pre-defined time to perform an action such as opening acontext-specific menu to make available additional options for the user136 to interact with the visualization 138.

In some embodiments, the input device 148 embodied as a touchscreen cansupport a pan gesture in which the user 136 places a finger on thetouchscreen and maintains contact with the touchscreen while moving thefinger on the touchscreen. The pan gesture may be used for variousreasons including, but not limited to, moving through or around thevisualization 138 at a controlled rate. Multiple finger pan gestures arealso contemplated. In some embodiments, the touchscreen supports a flickgesture in which the user 136 swipes a finger in the direction the user136 wants the screen to move. The flick gesture may be used for variousreasons including, but not limited to, scrolling horizontally orvertically through the visualization 138. In some embodiments, thetouchscreen supports a pinch and stretch gesture in which the user 136makes a pinching motion with two fingers (e.g., thumb and forefinger) onthe touchscreen or moves the two fingers apart. The pinch and stretchgesture may be used for various reasons including, but not limited to,zooming gradually in or out of the visualization 138.

Although the above gestures have been described with reference to theuse of one or more fingers for performing the gestures on the inputdevice 148 embodied as a touchscreen, other appendages such as toes orobjects such as styluses may be used to interact with the visualization138 via the touchscreen. As such, the above gestures should beunderstood as being illustrative and should not be construed as beinglimiting in any way. Moreover, the above gestures might findcounterparts in other technologies disclosed herein, including thoseuseable by the XR system 144.

The computer system 102 and the NVP 104 can be in communication with areal-time NVP monitoring system 150 that collects present state data152. The present state data 152 is a subset of the NVP data 106 that iscollected in real-time. Although the real-time NVP monitoring system 150is illustrated as a system, the functionality of the real-time NVPmonitoring system 150 can be implemented as a standalone application oras a component of the NVP monitoring application 116. As such, theillustrated embodiment should not be construed as being limiting in anyway.

The computer system 102 and the NVP 104 also can be in communicationwith a metrics collection system 154 that collects past state data 156.The past state data 156 is another subset of the NVP data 106 that iscollected based upon historical data about the NVP 104. Although metricscollection system 154 is illustrated as a system, the functionality ofthe metrics collection system 154 can be implemented as a standaloneapplication or as a component of the NVP monitoring application 116. Assuch, the illustrated embodiment should not be construed as beinglimiting in any way.

The computer system 102 and the NVP 104 also can be in communicationwith a predictive analysis system 158 that generates future state data160. The future state data 160 is another subset of the NVP data 106that is generated based upon predictions about the NVP 104. Although thepredictive analysis system 158 is illustrated as a system, thefunctionality of the predictive analysis system 158 can be implementedas a standalone application or as a component of the NVP monitoringapplication 116. As such, the illustrated embodiment should not beconstrued as being limiting in any way.

FIG. 1 illustrates one computer system 102, one NVP 104, one SDN network112, one operating system 114, one NVP monitoring application 116, onevisualization component 118, one user 136, one visualization 138, one UI140, one display 142, one XR system 144, one input device 148, onereal-time NVP monitoring system 150, one metrics collection system 154,and one predictive analysis system 158. It should be understood,however, that some implementations of the operating environment 100 caninclude multiple computer systems 102, multiple NVPs 104, multiple SDNnetworks 112, multiple operating systems 114, multiple NVP monitoringapplications 116, multiple visualization components 118, multiple users136, multiple visualizations 138, multiple UIs 140, multiple displays142, multiple XR systems 144, multiple input devices 148, multiplereal-time NVP monitoring systems 150, multiple metrics collectionsystems 154, and/or multiple predictive analysis systems 158. As such,the illustrated embodiment of the operating environment 100 should beunderstood as being illustrative, and should not be construed as beinglimiting in any way.

Turning now to FIG. 2, additional aspects of the visualization component118 will be presented, according to one illustrative embodiment. Inparticular, FIG. 2 provides further details regarding architecture andsubcomponents of the visualization component 118, according to someembodiments. The visualization component 118 can include a number ofcomponents and/or subsystems including, but not limited to, an NVPvisualization control 200, an NVP visualization engine 202, and/or othercomponents and/or sub systems.

The NVP visualization control 200 can include functionality to receiveNVP data input 204, such as the NVP data 106 and/or subset thereof,including the present state data 152, the past state data 156, and thefuture state data 160, from the NVP 104. The NVP visualization control200 also can include functionality of a visualization user interface 206used to generate and present the UI 140 described herein above, via thedisplay 142, and/or the XR system 144.

The NVP visualization engine 202 can include an engine core 208 forgenerating visualizations according to the concepts and technologiesdescribed herein, such as the visualization 138. The engine core 208 canutilize any software framework designed for the creation and developmentof graphics. Some example software frameworks include, but are notlimited to, AUTOCAD (available from AUTODESK), BLENDER (available fromthe open source BLENDER FOUNDATION), UNREAL ENGINE (available from EPICGAMES), UNITY (available from UNITY TECHNOLOGIES), CRYENGINE (availablefrom CRYTEK), HAVOK VISION ENGINE (available from HAVOK), otherproprietary software frameworks, open source software frameworks,combinations thereof, and the like.

The NVP visualization engine 202 also can include visualization assets210 for representing application, network link, and/or other resourceswithin visualizations; input and touch modules 212 for interpretingtouch and/or multi-touch commands as input; gesture modules 214 forinterpreting gesture commands as input; shaders 216 for providingshading of generated and/or rendered three-dimensional objects; andviews 218 functionality for representing and/or interacting withdifferent views of the visualization 138, including views representativeof the present state data 152, the past state data 156, and the futurestate data 160.

The visualization component 118 also can include various othercomponents and/or subsystems. For example, the visualization component118 can include the temporal management component 120. The visualizationcomponent 118 also can include various graphics plugins and/or APIs suchas the illustrated DIRECTX APIs, API call emulators, combinationsthereof, or the like. It should be appreciated that the visualizationcomponent 118 can include additional and/or alternative functionalitynot shown in FIG. 2. As such, the embodiment illustrated in FIG. 2should be understood as being illustrative and should not be construedas being limiting in any way.

Turning now to FIGS. 3A-3F, diagrams illustrating aspects of variousaspects of an example visualization, such as the visualization 138, willbe described, according to embodiments. Turning first to FIG. 3A, aconnectivity view 300 shows a plurality of the applications 110interconnected via at least a portion of the SDN network 112. Theapplications 110 are represented as circles of varying gray-scaleshades. The SDN network 112 is represented as connection linesconnecting the applications 110.

Turning now to FIG. 3B, a full view 302 (also referred to herein as aservice graph view) shows a collection of available resources (such asapplication resources embodied as the applications 110) along withsequencing and relationships available to be used to process data planeservice requests to instantiate a service instance of one or more of theservices 108. A service graph describes the actual topology of theresources instantiated and operationalized by the NVP 104 within the SDNnetwork 112. The full view 302 also shows a service path 304. Theservice path 304 shows a collection of specific resources from theservice graph along with sequencing and relationships used to process aspecific data plane service request. A service path describes a logicaltopology of the resources included in a particular instance of aservice, such as one of the services 108. The illustrated service path304 provided herein follows a flow convention of left-to-right.

A logical view of the service path 304 can be provided by a face planeview 306 of the visualization 138, such as in the example shown in FIG.3C. The visualization 138 can provide a plurality of layers of the faceplane view 306. In FIG. 3D, a slice view 308 of the visualization 138represents one of these layers. Each of the layers can represent aphysical technical plant (“TeP”) location within the NVP 104. A specificresource 310 in a specific TeP location that is processing a particulardata plane service request along the service path 304 can be identifiedby sliding out the corresponding layer for examination by the user 136or by navigating into the visualization 138. A top plane view 312 isshown in FIG. 3E. The top plane view 312 shows the service path 304across multiple layers of the face plane view—that is, multiple TePlocations within the NVP 104.

Turning now to FIG. 3F, a past view 326 is shown. The past view 326represents a past service graph view based upon a past collection ofresources (such as application resources embodied as the applications110) available at some time in the past along with sequencing andrelationships that were available to process data plane service requestsand to instantiate a service instance of one or more of the services 108in the past. The past view 326 describes a past actual topology of theresources instantiated and operationalized by the NVP 104 within the SDNnetwork 112 based upon the past state data 156. The past view 326 alsoshows a past state of the service path 304. The service path 304 shows acollection of specific resources along with sequencing and relationshipsused to process a specific data plane service request in the past.

Turning now to FIG. 3G, a present view 314 is shown. The present view314 represents a present service graph view based upon a presentcollection of resources (such as application resources embodied as theapplications 110) currently available along with sequencing andrelationships that are available to process data plane service requestsand to instantiate a service instance of one or more of the services108. The present view 314 describes the present actual topology of theresources currently instantiated and operationalized by the NVP 104within the SDN network 112 based upon the present state data 152. Thepresent view 314 also shows a present state the service path 304. Theservice path 304 shows a present collection of specific resources alongwith sequencing and relationships used to process a specific data planeservice request.

Turning now to FIG. 3H, a future view 316 is shown. The future view 316represents a future service graph view based upon a future collection ofresources (such as application resources embodied as the applications110) predicted to be available in the future along with sequencing andrelationships that are predicted to be available to process data planeservice requests and to instantiate a service instance of one or more ofthe services 108. The future view 316 describes a future actual topologyof the resources to be instantiated and operationalized by the NVP 104within the SDN network 112 based upon the future state data 160. Thefuture view 316 also shows the service path 304. The service path 304shows a future collection of specific resources along with sequencingand relationships to be used to process a specific data plane servicerequest.

FIGS. 3F-3H also illustrate a temporal management function 318 that iscreated and managed by the temporal management component 120. The user136 can interact with the temporal management function 318 to select aspecific time, including a time in the past, present, or future, and tobe presented with either the past view 326, the present view 314, or thefuture view 316 based upon the selection. In the illustrated example,the temporal management function 318 includes a timeline 320 with timeintervals in one year increments, although the temporal managementfunction 318 may include different time increments such as seconds,minutes, days, hours, weeks, months, or any division or multiplethereof. Moreover, the illustrated example of the temporal managementfunction 318 shows a pointer 322 that the user 136 can interact with(e.g., select with a mouse, keyboard, or touchscreen) to select aspecific time from which to view the visualization 138. The illustratedtemporal management function 318 also includes a temporal managementcontrol 324 with controls for moving/scrubbing through the timeline 320.The illustrated example for the temporal management control 324 includescontrols for forward and reverse, and selecting different time periodand time units. Additional details about the temporal management control324 are illustrated and described herein below with reference to FIG.17. It is contemplated that the user 136 may be provided with additionalor alternative ways to interact with the temporal management function318, such as by way of gestures, other interactions, and/or other userinterface elements. The XR system 144 may provide additionalinteractivity with the temporal management function 318 such as the user136 flying through the visualization 138 as if flying to the past or thefuture.

Turning now to FIG. 4, aspects of a method 400 for generating avisualization 138 of the NVP 104 will be described, according to anillustrative embodiment. It should be understood that the operations ofthe methods disclosed herein are not necessarily presented in anyparticular order and that performance of some or all of the operationsin an alternative order(s) is possible and is contemplated. Theoperations have been presented in the demonstrated order for ease ofdescription and illustration. Operations may be added, omitted, and/orperformed simultaneously, without departing from the scope of theconcepts and technologies disclosed herein.

It also should be understood that the methods disclosed herein can beended at any time and need not be performed in its entirety. Some or alloperations of the methods, and/or substantially equivalent operations,can be performed by execution of computer-readable instructions includedon a computer storage media, as defined herein. The term“computer-readable instructions,” and variants thereof, as used herein,is used expansively to include routines, applications, applicationmodules, program modules, programs, components, data structures,algorithms, and the like. Computer-readable instructions can beimplemented on various system configurations including single-processoror multiprocessor systems, minicomputers, mainframe computers, personalcomputers, hand-held computing devices, microprocessor-based,programmable consumer electronics, combinations thereof, and the like.

Thus, it should be appreciated that the logical operations describedherein are implemented (1) as a sequence of computer implemented acts orprogram modules running on a computing system and/or (2) asinterconnected machine logic circuits or circuit modules within thecomputing system. The implementation is a matter of choice dependent onthe performance and other requirements of the computing system.Accordingly, the logical operations described herein are referred tovariously as states, operations, structural devices, acts, or modules.These states, operations, structural devices, acts, and modules may beimplemented in software, in firmware, in special purpose digital logic,and any combination thereof. As used herein, the phrase “cause aprocessor to perform operations” and variants thereof is used to referto causing a processor of the computer system 102, a processor of theNVP 104, a processor of the real-time NVP monitoring system 150, aprocessor of the metrics collection system 154, a processor of thepredictive analysis system 158, a processor of the XR system 144, aprocessor of the compute resources 126, and/or a processor one or moreother computing systems and/or devices disclosed herein to performoperations.

For purposes of illustrating and describing some of the concepts of thepresent disclosure, the methods disclosed herein are described as beingperformed via execution of one or more software modules. It should beunderstood that additional and/or alternative devices and/or networknodes can provide the functionality described herein via execution ofone or more modules, applications, and/or other software. Thus, theillustrated embodiments are illustrative, and should not be viewed asbeing limiting in any way.

The method 400 will be described with reference to FIG. 4 and furtherreference to FIGS. 1, 2, and 3A-3E. The method 400 begins and proceedsto operation 402. At operation 402, the computer system 102 obtains theNVP data input 204 associated with the NVP 104. The NVP data input 204can include the NVP data 106, the current state data 152, the past statedata 156, the future state data 160, or some combination thereof asshown in FIG. 2. From operation 402, the method 400 proceeds tooperation 404. At operation 404, the computer system 102 can generate,based upon the NVP data input 204, one or more visualizations of the NVPdata 106, such as the visualization 138 in one or more of the viewsillustrated in FIGS. 3A-3H. From operation 404, the method 400 proceedsto operation 406. At operation 406, the computer system 102 outputs thevisualization 138 to the display 142, and/or the XR system 144.

From operation 406, the method 400 proceeds to operation 408. Atoperation 408, the computer system 102 receives user input from the user136 via the visualization user interface 206 to perform one or moreactions to interact with the visualization 138. The actions can includeinput received by the computer system 102 via the display 142, the XRsystem 144, the input device(s) 148, or some combination thereof. Theactions can include movement actions such as, but not limited to, panup, pan down, pan left, pan right, rotate clockwise, rotatecounter-clockwise, tilt down, tilt up, zoom in, zoom out, field-of-viewincrease, field-of-view decrease, and the like. The movement actions canbe used to navigate the visualization 138, including moving back throughtime into the past to view past version of the visualization 138 andmoving forward through time into the future to view predicted futureversions of the visualization 138. Other actions to add, delete, and/ormodify at least a portion of the visualization 138 also arecontemplated. From operation 408, the method 400 proceeds to operation410. The method 400 can end at operation 410.

Turning now to FIG. 5, a method 500 for adjusting a view of avisualization 138 of the NVP 104 will be described in detail, accordingto an illustrative embodiment. The method 500 will be described from theperspective of the computer system 102.

The method 500 begins and proceeds to operation 502. At operation 502,the computer system 102 receives input from the user 136 to adjust aview of the visualization 138. In some embodiments, the visualizationuser interface 206 can present one or more user interface elements, eachof which can be representative of one or more of the views 218, someexamples of which are shown in FIGS. 3A-31I. For example, thevisualization user interface 206 may present thumbnail images that arerepresentative of each of the views. Text descriptions, icons, and thelike are also contemplated.

From operation 502, the method 500 proceeds to operation 504. Atoperation 504, the computer system 102 generates a new view of thevisualization 138 in accordance with the user input. Examples of someillustrative views are provided herein in FIGS. 3A-31I. From operation504, the method 500 proceeds to operation 506. At operation 506, thecomputer system 102 outputs the visualization 138 in the new view. Fromoperation 506, the method 500 proceeds to operation 508. The method 500can end at operation 508.

Turning now to FIG. 6, a method 600 for generating a logical topologyview of a visualization 138 of the NVP 104 when a new service or a newservice instance is instantiated by the NVP 104 will be described indetail, according to an illustrative embodiment. The method 600 will bedescribed from the perspective of the computer system 102.

The method 600 begins and proceeds to operation 602. At operation 602,the computer system 102 receives a request to instantiate a new serviceinstance for one of the services 108. From operation 602, the method 600proceeds to operation 604. At operation 604, the computer system 102generates a logical topology view, such as the face plane view 306 shownin FIG. 3C, for a service path representing the newly-instantiatedservice instance. From operation 604, the method 600 proceeds tooperation 606. At operation 606, the computer system 102 outputs thelogical topology view of the visualization 138. From operation 606, themethod 600 proceeds to operation 608. The method 600 can end atoperation 608.

Turning now to FIG. 7, a method 700 for generating actual topology viewof a visualization 138 of the NVP 104 in response to a request toutilize a service 108 will be described in detail, according to anillustrative embodiment. The method 700 will be described from theperspective of the computer system 102.

The method 700 begins and proceeds to operation 702. At operation 702,the computer system 102 receives a request to utilize one of theservices 108. From operation 702, the method 700 proceeds to operation704. At operation 704, the computer system 102 generates an actualtopology view, such as the slice view 308 shown in FIG. 3D. Fromoperation 704, the method 700 proceeds to operation 706. At operation706, the computer system 102 outputs the actual topology view of thevisualization 138. From operation 706, the method 700 proceeds tooperation 708. The method 700 can end at operation 708.

Turning now to FIG. 8, a method 800 for generating a past view 326 of avisualization 138 of the NVP 104 will be described in detail, accordingto an illustrative embodiment. The method 800 will be described from theperspective of the computer system 102 and the metrics collection system154.

The method 800 begins and proceeds to operation 802. At operation 802,the computer system 102 instructs the metrics collection system tocollect the past state data. In some embodiments, the computer system102 can instruct the metrics collection system to collect the past statedata periodically. In other embodiments, the computer system 102 caninstruct the metrics collection system to collect the past state databased upon a schedule.

From operation 802, the method 800 proceeds to operation 804. Atoperation 804, the computer system stores the past state data in amemory and/or other storage device. The computer system may store thepast state data locally and/or remotely. The past state data can includea time stamp associated with the time at which the past state data wascollected. The past state data therefore is representative of thevisualization at the specific past time identified by the time stamp.

From operation 804, the method 800 proceeds to operation 806. Atoperation 806, the computer system receives a request for a view of theNVP 104 in a past state (e.g., the past view 326 shown in FIG. 3F). Therequest can define a time and may be received through the temporalmanagement function. In the example of the past view 326 shown in FIG.3F, the temporal management function 318 is embodied as a timeline.Accordingly, the request may be derived from the user 136 moving thepointer 320 along the timeline 314 to the desired time. The temporalmanagement function 318 may be implemented in alternative ways asdescribed herein.

From operation 806, the method 800 proceeds to operation 808. Atoperation 808, the computer system obtains the past data associated withthe time defined in the request. In particular, the computer system mayquery the memory and/or other storage device in which the past statedata was stored at operation 804. The query can identify the time andthe memory and/or other storage device can provide the past dataassociated with the time stamp that matches the time.

From operation 808, the method 800 proceeds to operation 810. Atoperation 810, the computer system 102 generates a past view 326 of theNVP 104. From operation 810, the method 800 proceeds to operation 812.At operation 812, the computer system 102 outputs the past view 326 ofthe NVP 104. From operation 812, the method 800 proceeds to operation814. The method 800 can end at operation 814.

Turning now to FIG. 9, a method 900 for generating a present view 314 ofa visualization 138 of the NVP 104 will be described in detail,according to an illustrative embodiment. The method 900 will bedescribed from the perspective of the computer system 102 and thereal-time NVP monitoring system 150.

The method 900 begins and proceeds to operation 902. At operation 902,the computer system 102 instructs the real-time NVP monitoring system tocollect the present state data. In some embodiments, the computer system102 instructs the real-time NVP monitoring system to collect the presentstate data continuously such that the present state data is alwaysavailable to generate the present view 314. Moreover, this continuouscollection can enable the computer system 102 to generate the presentview 314 as an animated view that continually updates to reflectreal-time conditions of the NVP 104. In other embodiments, the computersystem 102 instructs the real-time NVP monitoring system to collect thepresent state data in response to a specific request.

From operation 902, the method 900 proceeds to operation 904. Atoperation 904, the computer system stores the present state data in amemory and/or other storage device. The computer system may store thepresent state data locally and/or remotely. The computer system maycontinually update the present state data stored in the memory and/orother storage device such that the present state data is alwaysrepresentative of the present state of the NVP 104. In some embodiments,the present state data can be time stamped and stored as past state datain addition to or as a substitute for the past state data 156 receivedfrom the metrics collection system 154. It is contemplated that thereal-time NVP monitoring system 150 may feed the present state data 152into the metrics collection system 154, which can time stamp the presentstate data 152 as part of the past state data 156. In this manner, theinteraction between the computer system 102 and real-time monitoringsystem 150 can be used exclusively for the exchange of the latest datathat is representative of the state of the NVP 104.

From operation 904, the method 900 proceeds to operation 906. Atoperation 906, the computer system receives a request for a view of thevisualization 138 of the NVP 104 in the present state. From operation906, the method 900 proceeds to operation 908. At operation 908, thecomputer system obtains the present state data from the memory and/orother storage device. From operation 908, the method 900 proceeds tooperation 910. At operation 910, the computer system 900 generates apresent view 314 of the NVP 104. In some embodiments, the present view314 can provide an animated view of the NVP 104. In these embodiments,the computer system may continuously obtain the present state data andgenerate frames of the present view 314 that can be presentedcontinuously as the present state data changes over time. From operation910, the method 900 proceeds to operation 912. At operation 912, thecomputer system 102 outputs the present view 314 of the NVP 104. Fromoperation 912, the method 900 proceeds to operation 914. The method 900can end at operation 914.

Turning now to FIG. 10, a method 1000 for generating a future view 316of the visualization 138 of the NVP 104 will be described in detail,according to an illustrative embodiment. The method 1000 will bedescribed from the perspective of the computer system 102 and thepredictive analysis system 158.

The method 1000 begins and proceeds to operation 1002. At operation1002, the computer system 102 instructs the predictive analysis system158 to predict the future state data 160. The predictive analysis system158 can implement one or more algorithms based upon the data (e.g., theNVP data 106) being analyzed. Some example algorithms include, but arenot limited to, a random number generator, an average of past values, amoving average, an exponential moving average, a Monte Carlo simulationtechnique, linear functions, and non-linear functions that may be usedto predict the future state data 160. In some embodiments, thepredictive analysis system 158 can utilize machine learning techniques,such as described herein below with reference to FIG. 16.

From operation 1002, the method 1000 proceeds to operation 1004. Atoperation 1004, the computer system 102 stores the future state data 160in a memory and/or other storage device. The computer system 102 maystore the future state data 160 locally and/or remotely. The futurestate data 160 can include a time stamp associated with the time forwhich the future state data 160 was predicted. The future state data 160therefore is representative of the visualization at the specific futuretime identified by the time stamp.

From operation 1004, the method 1000 proceeds to operation 1006. Atoperation 806, the computer system receives a request for a view of theNVP 104 in a future state (e.g., the future view 316 shown in FIG. 3G).The request can define a time and may be received through the temporalmanagement function. In the example of the future view 316 shown in FIG.3G, the temporal management function 318 is embodied as a timeline.Accordingly, the request may be derived from the user 136 moving thepointer 320 along the timeline 314 to the desired future time. Thetemporal management function 318 may be implemented in alternative waysas described herein.

From operation 1006, the method 1000 proceeds to operation 1008. Atoperation 1008, the computer system 102 obtains the future state data160 associated with the future time defined in the request. Inparticular, the computer system 102 may query the memory and/or otherstorage device in which the future state data 160 was stored atoperation 1004. The query can identify the time and the memory and/orother storage device can provide the future data associated with thetime stamp that matches the time.

From operation 1008, the method 1000 proceeds to operation 1010. Atoperation 1010, the computer system 102 generates a future view 316 ofthe NVP 104. From operation 1010, the method 1000 proceeds to operation1012. At operation 1012, the computer system 102 outputs the future view316 of the NVP 104. From operation 1012, the method 1000 proceeds tooperation 1014. The method 1000 can end at operation 1014.

Turning now to FIG. 11, a method 1100 for manipulating a visualization138 of the NVP 104 based upon time will be described in detail,according to an illustrative embodiment. The method 1100 will bedescribed from the perspective of the computer system 102. The method1100 begins and proceeds to operation 1102. At operation 1102, thecomputer system 102 obtains data associated with the NVP 104. This datacan include the present state data, the past state data, the futurestate data 160, or some combination thereof. From operation 1102, themethod 1100 proceeds to operation 1104. At operation 1104, the computersystem 102 generates the visualization 138 of the data associated withthe NVP 104. The initial version of the visualization 138 may begenerated based upon the present state data as default. The user 136 mayelect for the computer system 102 to generate the initial version of thevisualization 138 based upon the past state data or the future statedata 160. As such, the visualization user interface 206 can presentdifferent options for the type of data to be used to generate theinitial version of the visualization 138.

From operation 1104, the method 1100 proceeds to operation 1106. Atoperation 1106, the computer system 102 presents the temporal managementfunction. The temporal management function may be implemented indifferent ways such as a timeline as shown in FIGS. 3F-3H and/or otheruser interface elements. Regardless of the implementation details, thetemporal management function can include a plurality of selections thatare representative of the present state, the past state, and thepredicted future state of the NVP 104. As shown in FIGS. 3F-3H, thetemporal management function 318 includes selections based upon one yearincrements from 2018 to 2022, with the present state of the NVP 104shown as being associated with the year 2020.

From operation 1106, the method 1100 proceeds to operation 1108. Atoperation 1108, the computer system 102 receives a selection of thepresent state, the past state, or the predicted future state of the NVP104. As shown in FIGS. 3F-3H, the user 136 can make the selection bypositioning the pointer 320 along the temporal management function 318(shown as a timeline in the illustrated embodiment). It should beunderstood that the selection may be an ongoing process as the user 136moves the pointer 320 along the timeline.

From operation 1108, the method 1100 proceeds to operation 1110. Atoperation 1110, the computer system 102 manipulates the visualization inaccordance with the selection. In some embodiments, the computer system102 manipulates the visualization in real-time such that thevisualization 138 transitions from one state to another. This may appearas if the visualization is morphing from one state to another. Forexample, the user 136 may pause, fast forward (towards the futurestate), or rewind (towards the past state) by repositioning the pointer320 along the timeline. From operation 1110, the method 1100 proceeds tooperation 1112. At operation 1112, the computer system 102 outputs thevisualization. It should be understood that the operations 1108, 1110,and 1112 can be repeated as the user 136 continues to interact with thetemporal management function to manipulate the visualization throughtime.

From operation 1112, the method 1100 proceeds to operation 1114. Themethod 1100 can end at operation 1114.

Turning now to FIG. 12, a block diagram illustrating a plurality ofmodules 1200 associated with the NVP monitoring application 116 and thevisualization component 118 that can be executed by the computer system102 (all best shown in FIG. 1) to perform various operations tofacilitate user interaction with a visualization, such as thevisualization 138 (shown in FIG. 1), some illustrative examples of whichare shown in FIGS. 3A-3E, will be described. The plurality of modules1200 can be executed by the computer system 102 to perform servicemanagement operations, and specifically end-to-end service qualitymanagement (“E2E SQM”) visualization and control. The plurality ofmodules 1200 includes a service definition module 1202, a serviceelements topology assembly module 1204, a customer agreement module1206, a resource assignment module 1208, a service monitoring module1210, and a visualization and control module 1212. The plurality ofmodules 1200 can be interacted with by one or more users, such as theuser 136, who might be a service designer, a service engineer, a servicesalesperson, or the like.

The service definition module 1202 can allow a service designer todefine, via a user interface such as the user interface 140 (shown inFIG. 1), a service, such as one of the services 108 (also shown in FIG.1). The service definition module 1202 can provide input received fromthe service designer to the service elements topology assembly module1204. The service definition module 1202 can allow a service engineer toidentify service elements needed and a topology that chains the serviceelements in order to effect instances of the service when requested.

Based on overall end-to-end throughput that can be achieved fromresources needed to instantiate the service, a dimensioning profile canbe established by the resource assignment module 1208. The dimensioningprofile can set one or more objectives with regard to predictions ofend-to-end transaction throughput achieved by certain sizes of resourcesfor typical demand curves to within statistical availabilityrequirements (e.g., five 9's).

Salespeople can utilize the customer agreement module 1206 to gaincustomer's agreement to use the service. The resource assignment module1208 can provision resources and can provide the service based on thecustomer's anticipated level of demand in accordance with the customer'sagreement.

Once instantiated, the service monitoring module 1210 can monitor theservice for compliance with general objectives as well as specificagreements made with particular customers. The visualization and controlmodule 1212 can provide the visualization 138. The visualization 138 canprovide a way to visualize the currently active topology of aninstantiated service, the resource state of the service, and theend-to-end service quality being delivered to the customer. Thevisualization and control module 1212 also can provide the userinterface 140 for the control and adjustment of resources assigned bythe resource assignment module 1208 to provide or augment the serviceexecution, providing a closed-loop control system for adjusting QoS.

FIG. 13 is a block diagram illustrating a computer system 1300configured to provide the functionality in accordance with variousembodiments of the concepts and technologies disclosed herein. In someimplementations, at least a portion of the hardware resources in thehardware resource layer 121 (best illustrated in FIG. 1) are provided,at least in part, by one or more host server computers (collectively,“host server cluster”), which is/are configured like the architecture ofthe computer system 1300. It should be understood, however, thatmodification to the architecture may be made to facilitate certaininteractions among elements described herein. In some implementations,the compute resources 126, the memory resources 128 and/or the otherresources 130 are configured like the architecture of the computersystem 1300 or portions thereof. In some implementations, the computersystem 102, the XR system 144, the real-time NVP monitoring system 150,the metrics collection system 154, and/or the predictive analysis system158 is/are configured like the architecture of the computer system 1300or portions thereof.

The computer system 1300 includes a processing unit 1302, a memory 1304,one or more user interface devices 1306, one or more input/output(“I/O”) devices 1308, and one or more network devices 1310, each ofwhich is operatively connected to a system bus 1312. The bus 1312enables bi-directional communication between the processing unit 1302,the memory 1304, the user interface devices 1306, the I/O devices 1308,and the network devices 1310.

The processing unit 1302 may be a standard central processor thatperforms arithmetic and logical operations, a more specific purposeprogrammable logic controller (“PLC”), a programmable gate array, orother type of processor known to those skilled in the art and suitablefor controlling the operation of the server computer. Processing unitsare generally known, and therefore are not described in further detailherein. The compute resources 126 can include one or more instances ofthe processing units 1302.

The memory 1304 communicates with the processing unit 1302 via thesystem bus 1312. In some embodiments, the memory 1304 is operativelyconnected to a memory controller (not shown) that enables communicationwith the processing unit 1302 via the system bus 1312. The memoryresources 128 can include one or more instances of the memory 1304. Theillustrated memory 1304 includes an operating system 1314 and one ormore program modules 1316.

The operating system 1314 can include the operating system 114 of thecomputer system 102 best shown in FIG. 1. The operating system 1314 caninclude, but is not limited to, members of the WINDOWS, WINDOWS CE,and/or WINDOWS MOBILE families of operating systems from MICROSOFTCORPORATION, the LINUX family of operating systems, the SYMBIAN familyof operating systems from SYMBIAN LIMITED, the BREW family of operatingsystems from QUALCOMM CORPORATION, the MAC OS, OS X, and/or iOS familiesof operating systems from APPLE CORPORATION, the FREEBSD family ofoperating systems, the SOLARIS family of operating systems from ORACLECORPORATION, the ANDROID OS family of operating systems from GOOGLEINC., other operating systems, and the like.

The program modules 1316 may include various software and/or programmodules to perform the various operations described herein. For example,the program modules can include the NVP monitoring application 116 andthe visualization component 118 of the computer system 102 best shown inFIG. 1, and more particularly, the plurality of modules associated withthe method 800 described above with reference to FIG. 8. The programmodules 1316 and/or other programs can be embodied in computer-readablemedia containing instructions that, when executed by the processing unit1302, perform various operations such as those described herein.According to embodiments, the program modules 1316 may be embodied inhardware, software, firmware, or any combination thereof.

By way of example, and not limitation, computer-readable media mayinclude any available computer storage media or communication media thatcan be accessed by the computer system 1300. Communication mediaincludes computer-readable instructions, data structures, programmodules, or other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any delivery media. The term“modulated data signal” means a signal that has one or more of itscharacteristics changed or set in a manner as to encode information inthe signal. By way of example, and not limitation, communication mediaincludes wired media such as a wired network or direct-wired connection,and wireless media such as acoustic, RF, infrared and other wirelessmedia. Combinations of the any of the above should also be includedwithin the scope of computer-readable media.

Computer storage media includes volatile and non-volatile, removable andnon-removable media implemented in any method or technology for storageof information such as computer-readable instructions, data structures,program modules, or other data. Computer storage media includes, but isnot limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solidstate memory technology, CD-ROM, DVD, or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can be accessed by the computer system1300. In the claims, the phrase “computer storage medium,”“computer-readable storage medium,” and variations thereof does notinclude waves or signals per se and/or communication media, andtherefore should be construed as being directed to “non-transitory”media only.

The user interface devices 1306 may include one or more devices withwhich a user accesses the computer system 1300. The user interfacedevices 1306 may include, but are not limited to, computers, servers,personal digital assistants, cellular phones, or any suitable computingdevices. The I/O devices 1308 enable a user to interface with theprogram modules 1316. In one embodiment, the I/O devices 1308 areoperatively connected to an I/O controller (not shown) that enablescommunication with the processing unit 1302 via the system bus 1312. TheI/O devices 1308 may include one or more input devices, such as, but notlimited to, a keyboard, a mouse, or an electronic stylus. Further, theI/O devices 1308 may include one or more output devices, such as, butnot limited to, a display screen or a printer.

The network devices 1310 enable the computer system 1300 to communicatewith other networks or remote systems via a network 1318, which caninclude the SDN network 112 and/or other networks described herein.Examples of the network devices 1310 include, but are not limited to, amodem, a radio frequency (“RF”) or infrared (“IR”) transceiver, atelephonic interface, a bridge, a router, or a network card. The network1318 may include a wireless network such as, but not limited to, awireless local area network (“WLAN”), a wireless wide area network(“WWAN”), a wireless personal area network (“WPAN”) such as provided viaBLUETOOTH technology, a wireless metropolitan area network (“WMAN”) suchas a WiMAX network or metropolitan cellular network. Alternatively, thenetwork 1318 may be a wired network such as, but not limited to, a widearea network (“WAN”), a wired LAN such as provided via Ethernet, a wiredpersonal area network (“PAN”), or a wired metropolitan area network(“MAN”).

Turning now to FIG. 14, additional details of a network 1400, such asthe network 1318, are illustrated, according to an illustrativeembodiment. The network 1400 includes a cellular network 1402, a packetdata network 1404, for example, the Internet, and a circuit switchednetwork 1406, for example, a publicly switched telephone network(“PSTN”). The cellular network 1402 includes various components such as,but not limited to, base transceiver stations (“BTSs”), Node-B's ore-Node-B's, base station controllers (“B SCs”), radio networkcontrollers (“RNCs”), mobile switching centers (“MSCs”), mobilemanagement entities (“MMEs”), short message service centers (“SMSCs”),multimedia messaging service centers (“MMSCs”), home location registers(“HLRs”), home subscriber servers (“HSSs”), visitor location registers(“VLRs”), charging platforms, billing platforms, voicemail platforms,GPRS core network components, location service nodes, an IP MultimediaSubsystem (“IMS”), and the like. The cellular network 1402 also includesradios and nodes for receiving and transmitting voice, data, andcombinations thereof to and from radio transceivers, networks, thepacket data network 1404, and the circuit switched network 1406.

A mobile communications device 1408, such as, for example, the computersystem 102, a cellular telephone, a user equipment, a mobile terminal, aPDA, a laptop computer, a handheld computer, and combinations thereof,can be operatively connected to the cellular network 1402. The cellularnetwork 1402 can be configured as a 2G Global System for Mobilecommunications (“GSM”) network and can provide data communications viaGeneral Packet Radio Service (“GPRS”) and/or Enhanced Data rates for GSMEvolution (“EDGE”). Additionally, or alternatively, the cellular network1402 can be configured as a 3G Universal Mobile TelecommunicationsSystem (“UMTS”) network and can provide data communications via theHigh-Speed Packet Access (“HSPA”) protocol family, for example,High-Speed Downlink Packet Access (“HSDPA”), Enhanced UpLink (“EUL”)(also referred to as High-Speed Uplink Packet Access (“HSUPA”)), andHSPA+. The cellular network 1402 also is compatible with 4G mobilecommunications standards such as Long-Term Evolution (“LTE”), 5G mobilecommunications standards, or the like, as well as evolved and futuremobile standards.

The packet data network 1404 includes various devices, for example,servers, computers, databases, and other devices in communication withone another, as is generally known. The packet data network 1404 devicesare accessible via one or more network links. The servers often storevarious files that are provided to a requesting device such as, forexample, a computer, a terminal, a smartphone, or the like. Typically,the requesting device includes software (a “browser”) for executing aweb page in a format readable by the browser or other software. Otherfiles and/or data may be accessible via “links” in the retrieved files,as is generally known. In some embodiments, the packet data network 1404includes or is in communication with the Internet. The circuit switchednetwork 1406 includes various hardware and software for providingcircuit switched communications. The circuit switched network 1406 mayinclude, or may be, what is often referred to as a plain old telephonesystem (“POTS”). The functionality of a circuit switched network 1406 orother circuit-switched network are generally known and will not bedescribed herein in detail.

The illustrated cellular network 1402 is shown in communication with thepacket data network 1404 and a circuit switched network 1406, though itshould be appreciated that this is not necessarily the case. One or moreInternet-capable devices 1410, for example, the computer system 102, aPC, a laptop, a portable device, or another suitable device, cancommunicate with one or more cellular networks 1402, and devicesconnected thereto, through the packet data network 1404. It also shouldbe appreciated that the Internet-capable device 1410 can communicatewith the packet data network 1304 through the circuit switched network1406, the cellular network 1402, and/or via other networks (notillustrated).

As illustrated, a communications device 1412, for example, a telephone,facsimile machine, modem, computer, or the like, can be in communicationwith the circuit switched network 1406, and therethrough to the packetdata network 1404 and/or the cellular network 1402. It should beappreciated that the communications device 1412 can be anInternet-capable device, and can be substantially similar to theInternet-capable device 1410. In the specification, the network 1400 isused to refer broadly to any combination of the networks 1402, 1404,1406. It should be appreciated that substantially all of thefunctionality described with reference to the network 1400 can beperformed by the cellular network 1402, the packet data network 1404,and/or the circuit switched network 1406, alone or in combination withother networks, network elements, and the like.

Turning now to FIG. 15, an illustrative mobile device 1500 andcomponents thereof will be described. In some embodiments, the computersystem 102, the XR system 144, the real-time NVP monitoring system 150,the metrics collection system 154, and/or the predictive analysis system158 described above with reference to FIG. 1 can be configured as and/orcan have an architecture similar or identical to the mobile device 1500described herein in FIG. 15. It should be understood, however, that thecomputer system 102, the XR system 144, the real-time NVP monitoringsystem 150, the metrics collection system 154, and/or the predictiveanalysis system 158 may or may not include the functionality describedherein with reference to FIG. 15. While connections are not shownbetween the various components illustrated in FIG. 15, it should beunderstood that some, none, or all of the components illustrated in FIG.15 can be configured to interact with one other to carry out variousdevice functions. In some embodiments, the components are arranged so asto communicate via one or more busses (not shown). Thus, it should beunderstood that FIG. 15 and the following description are intended toprovide a general understanding of a suitable environment in whichvarious aspects of embodiments can be implemented, and should not beconstrued as being limiting in any way.

As illustrated in FIG. 15, the mobile device 1500 can include a display1502 for displaying data. According to various embodiments, the display1502 can be configured to display the visualization 138, variousgraphical user interface (“GUI”) elements, text, images, video,advertisements, prompts, virtual keypads and/or keyboards, messagingdata, notification messages, metadata, internet content, device status,time, date, calendar data, device preferences, map and location data,combinations thereof, and the like. The mobile device 1500 also caninclude a processor 1504 and a memory or other data storage device(“memory”) 1506. The processor 1504 can be configured to process dataand/or can execute computer-executable instructions stored in the memory1506. The computer-executable instructions executed by the processor1504 can include, for example, an operating system 1508 (e.g., theoperating system 114), one or more applications 1510 (e.g., the NVPmonitoring application 116, the visualization component 188, and thetemporal management component 120), other computer-executableinstructions stored in a memory 1506, or the like. In some embodiments,the applications 1510 also can include a UI application (not illustratedin FIG. 15).

The UI application (e.g., the UI 140) can interface with the operatingsystem 1508 to facilitate user interaction with functionality and/ordata stored at the mobile device 1500 and/or stored elsewhere. In someembodiments, the operating system 1508 can include a member of theSYMBIAN OS family of operating systems from SYMBIAN LIMITED, a member ofthe WINDOWS MOBILE OS and/or WINDOWS PHONE OS families of operatingsystems from MICROSOFT CORPORATION, a member of the PALM WEBOS family ofoperating systems from HEWLETT PACKARD CORPORATION, a member of theBLACKBERRY OS family of operating systems from RESEARCH IN MOTIONLIMITED, a member of the IOS family of operating systems from APPLEINC., a member of the ANDROID OS family of operating systems from GOOGLEINC., and/or other operating systems. These operating systems are merelyillustrative of some contemplated operating systems that may be used inaccordance with various embodiments of the concepts and technologiesdescribed herein and therefore should not be construed as being limitingin any way.

The UI application can be executed by the processor 1504 to aid a user,such as the user 136, in viewing and interacting with the visualization138, entering content, viewing account information, answering/initiatingcalls, entering/deleting data, entering and setting user IDs andpasswords for device access, configuring settings, manipulating addressbook content and/or settings, multimode interaction, interacting withother applications 1510, and otherwise facilitating user interactionwith the operating system 1508, the applications 1510, and/or othertypes or instances of data 1512 that can be stored at the mobile device1500.

According to various embodiments, the applications 1510 can include, forexample, presence applications, visual voice mail applications,messaging applications, text-to-speech and speech-to-text applications,add-ons, plug-ins, email applications, music applications, videoapplications, camera applications, location-based service applications,power conservation applications, game applications, productivityapplications, entertainment applications, enterprise applications,combinations thereof, and the like. The applications 1510, the data1512, and/or portions thereof can be stored in the memory 1506 and/or ina firmware 1514, and can be executed by the processor 1504. The firmware1514 also can store code for execution during device power up and powerdown operations. It can be appreciated that the firmware 1514 can bestored in a volatile or non-volatile data storage device including, butnot limited to, the memory 1506 and/or a portion thereof.

The mobile device 1500 also can include an input/output (“I/O”)interface 1516. The I/O interface 1516 can be configured to support theinput/output of data such as location information, user information,organization information, presence status information, user IDs,passwords, and application initiation (start-up) requests. In someembodiments, the I/O interface 1516 can include a hardwire connectionsuch as USB port, a mini-USB port, a micro-USB port, an audio jack, aPS2 port, an IEEE 1394 (“FIREWIRE”) port, a serial port, a parallelport, an Ethernet (RJ45) port, an RJ11 port, a proprietary port,combinations thereof, or the like. In some embodiments, the mobiledevice 1500 can be configured to synchronize with another device totransfer content to and/or from the mobile device 1500. In someembodiments, the mobile device 1500 can be configured to receive updatesto one or more of the applications 1510 via the I/O interface 1516,though this is not necessarily the case. In some embodiments, the I/Ointerface 1516 accepts I/O devices such as the input device(s) 148,keyboards, keypads, mice, interface tethers, printers, plotters,external storage, touch/multi-touch screens, touch pads, trackballs,joysticks, microphones, remote control devices, displays, projectors,medical equipment (e.g., stethoscopes, heart monitors, and other healthmetric monitors), modems, routers, external power sources, dockingstations, combinations thereof, and the like. It should be appreciatedthat the I/O interface 1516 may be used for communications between themobile device 1500 and a network device or local device.

The mobile device 1500 also can include a communications component 1518.The communications component 1518 can be configured to interface withthe processor 1504 to facilitate wired and/or wireless communicationswith one or more networks described above herein. In some embodiments,other networks include networks that utilize non-cellular wirelesstechnologies such as WI-FI or WIMAX. In some embodiments, thecommunications component 1518 includes a multimode communicationssubsystem for facilitating communications via the cellular network andone or more other networks.

The communications component 1518, in some embodiments, includes one ormore transceivers. The one or more transceivers, if included, can beconfigured to communicate over the same and/or different wirelesstechnology standards with respect to one another. For example, in someembodiments one or more of the transceivers of the communicationscomponent 1518 may be configured to communicate using GSM, code divisionmultiple access (“CDMA”), CDMAONE, CDMA2000, LTE, and various other 2G,2.5G, 3G, 4G, 5G, and greater generation technology standards. Moreover,the communications component 1518 may facilitate communications overvarious channel access methods (which may or may not be used by theaforementioned standards) including, but not limited to, time divisionmultiple access (“TDMA”), frequency division multiple access (“FDMA”),wideband CDMA (“W-CDMA”), orthogonal frequency-division multiplexing(“OFDM”), spatial division multiple access (“SDMA”), and the like.

In addition, the communications component 1518 may facilitate datacommunications using GPRS, EDGE, the HSPA protocol family, includingHSDPA, EUL, or otherwise termed HSUPA, HSPA+, and various other currentand future wireless data access standards. In the illustratedembodiment, the communications component 1518 can include a firsttransceiver (“TxRx”) 1520A that can operate in a first communicationsmode (e.g., GSM). The communications component 1518 also can include anN^(th) transceiver (“TxRx”) 1520N that can operate in a secondcommunications mode relative to the first transceiver 1520A (e.g.,UMTS). While two transceivers 1520A-N(hereinafter collectively and/orgenerically referred to as “transceivers 1520”) are shown in FIG. 15, itshould be appreciated that less than two, two, and/or more than twotransceivers 1520 can be included in the communications component 1518.

The communications component 1518 also can include an alternativetransceiver (“Alt TxRx”) 1522 for supporting other types and/orstandards of communications. According to various contemplatedembodiments, the alternative transceiver 1522 can communicate usingvarious communications technologies such as, for example, WI-FI, WIMAX,BLUETOOTH, infrared, infrared data association (“IRDA”), near-fieldcommunications (“NFC”), other radio frequency (“RF”) technologies,combinations thereof, and the like.

In some embodiments, the communications component 1518 also canfacilitate reception from terrestrial radio networks, digital satelliteradio networks, internet-based radio service networks, combinationsthereof, and the like. The communications component 1518 can processdata from a network such as the Internet, an intranet, a broadbandnetwork, a WI-FI hotspot, an Internet service provider (“ISP”), adigital subscriber line (“DSL”) provider, a broadband provider,combinations thereof, or the like.

The mobile device 1500 also can include one or more sensors 1524. Thesensors 1524 can include temperature sensors, light sensors, air qualitysensors, movement sensors, orientation sensors, noise sensors, proximitysensors, or the like. As such, it should be understood that the sensors1524 can include, but are not limited to, accelerometers, magnetometers,gyroscopes, infrared sensors, noise sensors, microphones, combinationsthereof, or the like. Additionally, audio capabilities for the mobiledevice 1500 may be provided by an audio I/O component 1526. The audioI/O component 1526 of the mobile device 1500 can include one or morespeakers for the output of audio signals, one or more microphones forthe collection and/or input of audio signals, and/or other audio inputand/or output devices.

The illustrated mobile device 1500 also can include a subscriberidentity module (“SIM”) system 1528. The SIM system 1528 can include auniversal SIM (“USIM”), a universal integrated circuit card (“UICC”)and/or other identity devices. The SIM system 1528 can include and/orcan be connected to or inserted into an interface such as a slotinterface 1530. In some embodiments, the slot interface 1530 can beconfigured to accept insertion of other identity cards or modules foraccessing various types of networks. Additionally, or alternatively, theslot interface 1530 can be configured to accept multiple subscriberidentity cards. Because other devices and/or modules for identifyingusers and/or the mobile device 1500 are contemplated, it should beunderstood that these embodiments are illustrative, and should not beconstrued as being limiting in any way.

The mobile device 1500 also can include an image capture and processingsystem 1532 (“image system”). The image system 1532 can be configured tocapture or otherwise obtain photos, videos, and/or other visualinformation. As such, the image system 1532 can include cameras, lenses,charge-coupled devices (“CCDs”), combinations thereof, or the like. Themobile device 1500 may also include a video system 1534. The videosystem 1534 can be configured to capture, process, record, modify,and/or store video content. Photos and videos obtained using the imagesystem 1532 and the video system 1534, respectively, may be added asmessage content to a multimedia message service (“MIMS”) message, emailmessage, and sent to another mobile device. The video and/or photocontent also can be shared with other devices via various types of datatransfers via wired and/or wireless communication devices as describedherein.

The mobile device 1500 also can include one or more location components1536 (e.g., the location component(s) 158). The location components 1536can be configured to send and/or receive signals to determine ageographic location of the mobile device 1500. According to variousembodiments, the location components 1536 can send and/or receivesignals from GPS devices, A-GPS devices, WI-FI/WIMAX and/or cellularnetwork triangulation data, combinations thereof, and the like. Thelocation component 1536 also can be configured to communicate with thecommunications component 1518 to retrieve triangulation data fordetermining a location of the mobile device 1500. In some embodiments,the location component 1536 can interface with cellular network nodes,telephone lines, satellites, location transmitters and/or beacons,wireless network transmitters and receivers, combinations thereof, andthe like. In some embodiments, the location component 1536 can includeand/or can communicate with one or more of the sensors 1524 such as acompass, an accelerometer, and/or a gyroscope to determine theorientation of the mobile device 1500. Using the location component1536, the mobile device 1500 can generate and/or receive data toidentify its geographic location, or to transmit data used by otherdevices to determine the location of the mobile device 1500. Thelocation component 1536 may include multiple components for determiningthe location and/or orientation of the mobile device 1500.

The illustrated mobile device 1500 also can include a power source 1538.The power source 1538 can include one or more batteries, power supplies,power cells, and/or other power subsystems including alternating current(“AC”) and/or direct current (“DC”) power devices. The power source 1538also can interface with an external power system or charging equipmentvia a power I/O component 1540. Because the mobile device 1500 caninclude additional and/or alternative components, the above embodimentshould be understood as being illustrative of one possible operatingenvironment for various embodiments of the concepts and technologiesdescribed herein. The described embodiment of the mobile device 1500 isillustrative, and should not be construed as being limiting in any way.

Turning now to FIG. 16, a machine learning system 1600 capable ofimplementing aspects of the embodiments disclosed herein will bedescribed. In some embodiments, the computer system 102, the XR system144, the real-time NVP monitoring system 150, the metrics collectionsystem 154, and/or the predictive analysis system 158 can be configuredto include or to utilize the machine learning system 1600.

The illustrated machine learning system 1600 includes one or moremachine learning models 1602. The machine learning models 1602 caninclude supervised and/or semi-supervised learning models. The machinelearning model(s) 1602 can be created by the machine learning system1600 based upon one or more machine learning algorithms 1604. Themachine learning algorithm(s) 1604 can be any existing, well-knownalgorithm, any proprietary algorithms, or any future machine learningalgorithm. Some example machine learning algorithms 1604 include, butare not limited to, gradient descent, linear regression, logisticregression, linear discriminant analysis, classification tree,regression tree, Naive Bayes, K-nearest neighbor, learning vectorquantization, support vector machines, and the like. Classification andregression algorithms might find particular applicability to theconcepts and technologies disclosed herein. The machine learningalgorithm(s) 1604 can include one or more predictive analysisalgorithms, some examples of which include, but are not limited to, arandom number generator, an average of past values, a moving average, anexponential moving average, a Monte Carlo simulation technique, linearfunctions, and non-linear functions that may be used to predict thefuture state data 160. Those skilled in the art will appreciate theapplicability of various machine learning algorithms 1604 based upon theproblem(s) to be solved by machine learning via the machine learningsystem 1600.

The machine learning system 1600 can control the creation of the machinelearning models 1602 via one or more training parameters. In someembodiments, the training parameters are selected modelers at thedirection of an enterprise, for example. Alternatively, in someembodiments, the training parameters are automatically selected basedupon data provided in one or more training data sets 1606. The trainingparameters can include, for example, a learning rate, a model size, anumber of training passes, data shuffling, regularization, and/or othertraining parameters known to those skilled in the art.

The learning rate is a training parameter defined by a constant value.The learning rate affects the speed at which the machine learningalgorithm 1604 converges to the optimal weights. The machine learningalgorithm 1604 can update the weights for every data example included inthe training data set 1606. The size of an update is controlled by thelearning rate. A learning rate that is too high might prevent themachine learning algorithm 1604 from converging to the optimal weights.A learning rate that is too low might result in the machine learningalgorithm 1604 requiring multiple training passes to converge to theoptimal weights.

The model size is regulated by the number of input features (“features”)1606 in the training data set 1606. A greater the number of features1608 yields a greater number of possible patterns that can be determinedfrom the training data set 1606. The model size should be selected tobalance the resources (e.g., compute, memory, storage, etc.) needed fortraining and the predictive power of the resultant machine learningmodel 1602.

The number of training passes indicates the number of training passesthat the machine learning algorithm 1604 makes over the training dataset 1606 during the training process. The number of training passes canbe adjusted based, for example, on the size of the training data set1606, with larger training data sets being exposed to fewer trainingpasses in consideration of time and/or resource utilization. Theeffectiveness of the resultant machine learning model 1602 can beincreased by multiple training passes.

Data shuffling is a training parameter designed to prevent the machinelearning algorithm 1604 from reaching false optimal weights due to theorder in which data contained in the training data set 1606 isprocessed. For example, data provided in rows and columns might beanalyzed first row, second row, third row, etc., and thus an optimalweight might be obtained well before a full range of data has beenconsidered. By data shuffling, the data contained in the training dataset 1606 can be analyzed more thoroughly and mitigate bias in theresultant machine learning model 1602.

Regularization is a training parameter that helps to prevent the machinelearning model 1602 from memorizing training data from the training dataset 1606. In other words, the machine learning model 1602 fits thetraining data set 1606, but the predictive performance of the machinelearning model 1602 is not acceptable. Regularization helps the machinelearning system 1600 avoid this overfitting/memorization problem byadjusting extreme weight values of the features 1608. For example, afeature that has a small weight value relative to the weight values ofthe other features in the training data set 1606 can be adjusted tozero.

The machine learning system 1600 can determine model accuracy aftertraining by using one or more evaluation data sets 1610 containing thesame features 1608′ as the features 1608 in the training data set 1606.This also prevents the machine learning model 1602 from simplymemorizing the data contained in the training data set 1606. The numberof evaluation passes made by the machine learning system 1600 can beregulated by a target model accuracy that, when reached, ends theevaluation process and the machine learning model 1602 is consideredready for deployment.

After deployment, the machine learning model 1602 can perform aprediction operation (“prediction”) 1614 with an input data set 1612having the same features 1608″ as the features 1608 in the training dataset 1606 and the features 1608′ of the evaluation data set 1610. Theresults of the prediction 1614 are included in an output data set 1616consisting of predicted data. The machine learning model 1602 canperform other operations, such as regression, classification, andothers. As such, the example illustrated in FIG. 16 should not beconstrued as being limiting in any way.

Turning now to FIG. 17, a diagram illustrating the temporal managementcontrol 324 that allows the user 136 to control the playback of thevisualization 138 will be described, according to an illustrativeembodiment. The illustrated temporal management control 324 shows, in acurrent date/time control 1700, the current date associated with thedata (e.g., the NVP data 106) being visualized. The current date/timecontrol 1700 may be selected to reveal a calendar/entry control to allowthe user 136 to directly select the date/time of the data to bevisualized. The current granularity of playback data “buckets” can beselected from a playback time period selector 1702. When the user 136selects the playback time period selector 1702, a drop-down menu orother UI element can allow the user 136 to select the day, week, month,or year as the unit of time to be used during playback. A single stepreverse control 1704 can be used to “rewind” to show the data from theprevious time period. Selecting a playback time unit selector 1706allows the user 136 to select desired time units such as 0.05 second (20frames per second), 0.1 second (10 frames per second), 1 second, 5seconds, and so on, where larger values represent a slower playbackspeed. A reverse continuous playback/pause control 1708 is used totoggle playback in reverse, whereas a forward continuous playback/pausecontrol 1710 is used to advance the visualization 138 to the next timeperiod at a rate selected by the playback time unit selector 1706, whereeach “frame” of the visualization 138 represents an advancement in timeapproximately equal to the playback time period selector 1702. The valuepresented for a metric is determined by an algorithm that uses thevalues of the metric over that time period. For example, if data iscaptured daily but the time period is “Weekly,” the algorithm will haveto determine how to compute the seven samples into a value to bedisplayed to the user 136. Example algorithms include, but are notlimited to, average, weighted average, first in, or last out. A singlestep forward control 1712 is used to advance the visualization 138 timeperiod by one unit of time indicated in the playback time periodselector 1702.

Based on the foregoing, it should be appreciated that concepts andtechnologies directed to time-based visualizations for NVPs have beendisclosed herein. Although the subject matter presented herein has beendescribed in language specific to computer structural features,methodological and transformative acts, specific computing machinery,and computer-readable media, it is to be understood that the conceptsand technologies disclosed herein are not necessarily limited to thespecific features, acts, or media described herein. Rather, the specificfeatures, acts and mediums are disclosed as example forms ofimplementing the concepts and technologies disclosed herein.

The subject matter described above is provided by way of illustrationonly and should not be construed as limiting. Various modifications andchanges may be made to the subject matter described herein withoutfollowing the example embodiments and applications illustrated anddescribed, and without departing from the true spirit and scope of theembodiments of the concepts and technologies disclosed herein.

The invention claimed is:
 1. A method comprising: obtaining, by acomputer system comprising a processor, from a real-time networkvirtualization platform monitoring system operating in communicationwith a network virtualization platform, present state data associatedwith a present state of the network virtualization platform, wherein thepresent state data is collected in real-time by the real-time networkvirtualization platform monitoring system, and wherein the present statedata is associated with the present state of a service provided, atleast in part, by an application operating within a software-definednetwork created and managed, at least in part, by the networkvirtualization platform; obtaining, by the computer system, from ametrics collection system operating in communication with the networkvirtualization platform, past state data associated with a past state ofthe network virtualization platform, wherein the past state data iscollected based upon historical data about the network virtualizationplatform, and wherein the past state data is associated with the paststate of the service provided, at least in part, by the applicationoperating within the software-defined network created and managed, atleast in part, by the network virtualization platform; obtaining, by thecomputer system, from a predictive analysis system operating incommunication with the network virtualization platform, future statedata that is associated with a predicted future state of the networkvirtualization platform, wherein the future state data is generated bythe predictive analysis system based upon a prediction about the networkvirtualization platform, and wherein the future state data is associatedwith the predicted future state of the service provided, at least inpart, by the application operating within the software-defined networkcreated and managed, at least in part, by the network virtualizationplatform; generating, by the computer system, a visualization of thepresent state data, the past state data, and the future state dataassociated with the network virtualization platform, wherein thevisualization comprises a three-dimensional visualization, thethree-dimensional visualization comprises a central cube visualization,the central cube visualization comprises a plurality of smaller cubevirtualizations, the plurality of smaller cube virtualizations comprisesa plurality of nodes representative of a plurality of applications, andeach of the plurality of applications is executable by at least aportion of a plurality of resources of the network virtualizationplatform; presenting, by the computer system, a temporal managementfunction comprising a plurality of selections representative of thepresent state, the past state, and the predicted future state of thenetwork virtualization platform; receiving, by the computer system viathe temporal management function, a selection, from the plurality ofselections, of the present state, the past state, or the predictedfuture state; manipulating, by the computer system, the visualization inaccordance with the selection; and outputting, by the computer system,the visualization.
 2. The method of claim 1, wherein the central cubevisualization further comprises a plurality of networking links betweenat least a portion of the plurality of applications of the plurality ofsmaller cube virtualizations.
 3. The method of claim 2, wherein thepresent state data, the past state data, and the future state data eachfurther comprise a topology of the plurality of resources of the networkvirtualization platform.
 4. The method of claim 1, wherein presentingthe temporal management function comprises presenting a timeline; andwherein each of the plurality of selections comprises a time interval.5. The method of claim 1, wherein manipulating the visualization inaccordance with the selection comprises transitioning, at least in part,between the present state, the past state, and the future state.
 6. Acomputer-readable storage medium having instructions stored thereonthat, when executed by a computer system, cause the computer system toperform operations comprising: obtaining, from a real-time networkvirtualization platform monitoring system operating in communicationwith a network virtualization platform, present state data associatedwith a present state of the network virtualization platform, wherein thepresent state data is collected by the real-time network virtualizationplatform monitoring system in real-time, and wherein the present statedata is associated with the present state of a service provided, atleast in part, by an application operating within a software-definednetwork created and managed, at least in part, by the networkvirtualization platform; obtaining, from a metrics collection systemoperating in communication with the network virtualization platform,past state data associated with a past state of the networkvirtualization platform, wherein the past state data is collected basedupon historical data about the network virtualization platform, andwherein the past state data is associated with the past state of theservice provided, at least in part, by the application operating withinthe software-defined network created and managed, at least in part, bythe network virtualization platform; obtaining, from a predictiveanalysis system operating in communication with the networkvirtualization platform, future state data associated with a predictedfuture state of the network virtualization platform, wherein the futurestate data is generated by the predictive analysis system based upon aprediction about the network virtualization platform, and wherein thefuture state data is associated with the predicted future state of theservice provided, at least in part, by the application operating withinthe software-defined network created and managed, at least in part, bythe network virtualization platform; generating a visualization of thepresent state data, the past state data, and the future state dataassociated with the network virtualization platform, wherein thevisualization comprises a three-dimensional visualization, thethree-dimensional visualization comprises a central cube visualization,the central cube visualization comprises a plurality of smaller cubevirtualizations, the plurality of smaller cube virtualizations comprisesa plurality of nodes representative of a plurality of applications; andeach of the plurality of applications is executable by at least aportion of a plurality of resources of the network virtualizationplatform; presenting a temporal management function comprising aplurality of selections representative of the present state, the paststate, and the predicted future state of the network virtualizationplatform; receiving, via the temporal management function, a selection,from the plurality of selections, of the present state, the past state,or the predicted future state; manipulating the visualization inaccordance with the selection; and outputting the visualization.
 7. Thecomputer-readable storage medium of claim 6, wherein the present statedata, the past state data, and the future state data each furthercomprise a topology of a plurality of resources of the networkvirtualization platform.
 8. The computer-readable storage medium ofclaim 6, wherein the central cube visualization further comprises aplurality of networking links between at least a portion of theplurality of applications of the plurality of smaller cubevirtualizations.
 9. The computer-readable storage medium of claim 6,wherein presenting the temporal management function comprises presentinga timeline; and wherein each of the plurality of selections comprises atime interval.
 10. The computer-readable storage medium of claim 6,wherein manipulating the visualization in accordance with the selectioncomprises transitioning, at least in part, between the present state,the past state, and the future state.
 11. A computer system comprising:a processor; and a memory comprising instructions that, when executed bythe processor, cause the processor to perform operations comprisingobtaining, from a real-time network virtualization platform monitoringsystem operating in communication with a network virtualizationplatform, present state data associated with a present state of thenetwork virtualization platform, wherein the present state data iscollected by the real-time network virtualization platform monitoringsystem in real-time, and wherein the present state data is associatedwith the present state of a service provided, at least in part, by anapplication operating within a software-defined network created andmanaged, at least in part, by the network virtualization platform,obtaining, from a metrics collection system operating in communicationwith the network virtualization platform, past state data associatedwith a past state of the network virtualization platform, wherein thepast state data is collected based upon historical data about thenetwork virtualization platform, and wherein the past state data isassociated with the past state of the service provided, at least inpart, by the application operating within the software-defined networkcreated and managed, at least in part, by the network virtualizationplatform, obtaining, from a predictive analysis system operating incommunication with the network virtualization platform, future statedata associated with a predicted future state of the networkvirtualization platform, wherein the future state data is generated bythe predictive analysis system based upon a prediction about the networkvirtualization platform, and wherein the future state data is associatedwith the predicted future state of the service provided, at least inpart, by the application operating within the software-defined networkcreated and managed, at least in part, by the network virtualizationplatform, generating a visualization of the present state data, the paststate data, and the future state data associated with the networkvirtualization platform, wherein the visualization comprises athree-dimensional visualization, the three-dimensional visualizationcomprises a central cube visualization, the central cube visualizationcomprises a plurality of smaller cube virtualizations, the plurality ofsmaller cube virtualizations comprises a plurality of nodesrepresentative of a plurality of applications, and each of the pluralityof applications is executable by at least a portion of a plurality ofresources of the network virtualization platform, presenting a temporalmanagement function comprising a plurality of selections representativeof the present state, the past state, and the predicted future state ofthe network virtualization platform, receiving, via the temporalmanagement function, a selection, from the plurality of selections, ofthe present state, the past state, or the predicted future state,manipulating the visualization in accordance with the selection, andoutputting the visualization.
 12. The computer system of claim 11,wherein the central cube visualization further comprises a plurality ofnetworking links between at least a portion of the plurality ofapplications of the plurality of smaller cube virtualizations.
 13. Thecomputer system of claim 12, wherein the present state data, the paststate data, and the future state data each further comprise a topologyof the plurality of resources of the network virtualization platform.14. The computer system of claim 11, wherein presenting the temporalmanagement function comprises presenting a timeline; and wherein each ofthe plurality of selections comprises a time interval.
 15. The computersystem of claim 11, wherein manipulating the visualization in accordancewith the selection comprises transitioning, at least in part, betweenthe present state, the past state, and the future state.